MetLife and Exception-Handling

Problem:

A large insurer recognized that any automated process was going to have exceptions — invalid or bad data that still needed humans to process it. Even with the promise of automation, manual work was needed to clean up not-in-good order data, which increased operational costs, slowed processing time, and increased the time it took to process beneficiary designation forms. And internal sta wanted an easier way to flag invalid data and correct it quickly to maintain daily service level agreements.

Solution:

In addition to Captricity’s AI engine for capturing data, an internal team at Captricity designed and deployed an streamlined exception-handling AI interface that prioritizes the right data for human review and contextualizes it with just enough information to make a fast and accurate decision. Metlife staff now had the ability to audit and correct incoming documents in an intuitive and simple interface. The results? Metlife increased straight-through automation by 42%, reduced processing time per form by over 50%, and reduced the time spent on manual exception handling by 70%.